• Journal of Korean Society of Water and Wastewater
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• v.25 no.3
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• pp.407-417
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• 2011

Nowadays, the high land use, mainly used for urbanization, is affecting runoff loads of non-point pollutants to increase. According to this fact, increasing runoff loads seems like to appear that it contributes to high ratio of pollution loads in the whole the pollution loads and that this non-point source is the main cause of water becoming worse quality. Especially, concentrated pollutants on the impermeable roads run off to the public water bodies. Also the coefficient of runoff from roads is high with a fast velocity of runoff, which ends up with consequence that a lot of pollutants runoff happens when it is raining. Therefore it is very important project to evaluate the quantity of pollutant loads. In this study, I computed the pollutant loadings depending on time and rainfall to analyze characteristics of runoff while first flush storm water and evaluated the runoff time while first flush storm water and rainfall based on the change in curves on the graph. I also computed contribution ratio to identify its impact on water quality of stream. I realized that the management and treatment of first flush storm water effluents is very important for the management of road's non-point source pollutants because runoff loads of non-point source pollution are over the 80% of whole loads of stream. Also according to the evaluation of runoff loads of first flush storm water for SS, run off time was shown under the 30 minute and rainfall was shown under the 5mm which is less than 20% of whole rainfall. These are under 5mm which is regarded amount of first flush storm water by the Ministry of Environment and it is judged to be because run off by rainfall is very fast on impermeable roads. Also, run off time and rainfall of BOD is higher than SS. Therefore I realized that the management of non-point source should be managed and done differently depending on each material. Finally, the contribution ratio of pollutants loads by rainfall-runoff was shown SS 12.7%, BOD 12.7%, COD 15.9%, T-N 4.9%, T-P 8.9%, however, the pollutants loads flowing into the steam was shown 4.4%. This represents that the concentration of non-point pollutants is relatively higher and we should find the methodical management and should be concerned about non-point source for improvement on water quality of streams.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.3_4
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• pp.34-47
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• 1995

It is experienced fact as a regular annual event that the structure to he designed on unreasonable flood for the agricultural structures including reservoirs have been brought not only loss of lives, but also enormous property damage. For the solution of this problem at issue, this study was conducted to develop an optimal runoff hydrograph model by comparison of the peak flows and time to peak between observed and simulated flows derived by linear time-invariant and linear time-variant models under the condition of having a short duration of heavy rainfall with uniform rainfall intensity at nine small watersheds which are within the range of 55.9 to 140.7 square kilometers in area in Han, Geum, Nagdong and Yeongsan Rivers. The results obtained through this study can be summarized as follows. 1. Storage constants and Gamma function arguments were calculated within the range of 1.2 to 6.42 and of 1.28 to 8.05 respectively by the moment method as the parameters for the analysis of runoff hydrograph based on linear time-invariant model. 2. Parameters for both linear time-invariant and linear time-variant models were calibrated with nine gaged watershed data, using a trial and error method. The resulting parameters including Gamma function argument, N and storage constant, K for linear time-invariant model were related statistically to watershed characteristic variables such as area, slope, length of main stream and the centroid length of the basin. 3. Average relative errors of the simulated peak discharge of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 0.75 and 5.42 percent respectively to the peak of observed runoff hydrographs. Correlation coefficients for the statistical analysis in the same condition were shown to be 0.999 and 0.978 with a high significance respectively. Therefore, it can be concluded that the accuracy of a linear time-variant model is approaching more closely to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 4. Average relative errors of the time to peak of calibrated runoff hydrographs by using linear time-variant and linear time-invariant models were shown to be 16.44 and 19.89 percent respectively to the time to peak of observed runoff hydrographs. Correlation coefficients in the same condition were also shown to be 0.999 and 0.886 with a high significance respectively. 5. It can be seen that the shape of simulated hydrograph based on a linear time- variant model is getting closer to the observed runoff hydrograph than that of a linear time-invariant model in the applied watersheds. 6. Two different models were verified with different rainfall-runoff events from data for the calibration by relative error and correlation analysis. Consequently, it can be generally concluded that verification results for the peak discharge and time to peak of simulated runoff hydrographs were in good agreement with those of calibrated runoff hydrographs.

• Journal of Korea Water Resources Association
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• v.52 no.9
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• pp.615-626
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• 2019

Soil moisture and runoff have very close relationship. Especially the water retention capacity and drainage characteristics of the soil are determined by various factors of the soil. In this study, a total of 40 rainfall events were identified from the entire rainfall events of Sulma basin in 2016 and 2017. For each selected events, the constant-K method was used to separate direct runoff and baseflow from total flow and calculate the runoff coefficient which shows positive exponential curve with Antecedent Soil Moisture (ASM). In addition to that, the threshold of soil moisture was determined at the point where the runoff coefficient starts increasing dramatically. The threshold of soil moisture shows great correlation with runoff and depth to water table. It was founded that not only ASM but also various factors, such as Initial Soil Moisture (ISM), storage capacity of soil and precipitation, affect the results of runoff response. Furthermore, wet condition and dry condition are separated by ASM threshold and the start and peak response are analyzed. And the results show that the response under wet condition occurred more quickly than that of dry condition. In most events occurred in dry condition, factors reached peak in order of soil moisture, depth to water table and runoff. However, in wet condition, they reached peak in order of depth to water table, runoff and soil moisture. These results will help identify the interaction among factors which affect the runoff, and it will help establish the relationship between various soil conditions and runoff.

• Journal of Korea Water Resources Association
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• v.56 no.1
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• pp.35-43
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• 2023

Future runoff analysis is influenced by climate change scenarios and hydrologic model parameters, with uncertainties. In this study, the uncertainty of future runoff analysis according to the shared socioeconomic pathway (SSP) scenario and hydrologic model parameters was analyzed. Among the SSP scenarios, the SSP2-4.5 and SSP5-8.5 scenarios were used, and the soil and water assessment tool (SWAT) model was used as the hydrologic model. For the parameters of the SWAT model, a total of 11 parameter were optimized to the observed runoff data using SWAT-CUP. Then, uncertainty analysis of future estimated runoff compared to the observed runoff was performed using jensen-shannon divergence (JS-D), which can calculate the difference in distribution. As a result, uncertainty of future runoff was analyzed to be larger in SSP5-8.5 than in SSP2-4.5, and larger in the far future (2061-2100) than in the near future (2021-2060). In this study, the uncertainty of future runoff using future climate data according to the parameters of the hydrologic model is as follows. Uncertainty was greatly analyzed when parameters used observed runoff data in years with low flow rates compared to average years. In addition, the uncertainty of future runoff estimation was analyzed to be greater for the parameters of the period in which the change in runoff compared to the average year was greater.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.484-489
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• 1998

The GLEAMS nutrient submodel was evaluated to predict nutrient losses in surface runoff following application of two rates (9 and 18 t/ha) of poultry litter and a recommended rate of commercial fertilizer on corn plots. Nutrient submodel was evaluated with calibrated runoff and sediment losses to the observed field data. Simulation of nitrogen transformation effects on nitrogen losses in surface runoff did not agree with field data. The model simulated higher NH$_4$-N than NO$_3$-N losses in surface runoff, while field data showed the opposite.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.419-422
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• 2003

The Sumjin Reservoir watershed was simulated by the SSARR model. In order to calibrate the parameters of SSARR model, watershed was divided into three sub-basins with the basin characteristics and the observed runoff datum at estuary of dam were used. As the Results of study, there was not much of difference between the observed runoff and the simulated runoff.

• Journal of Industrial Technology
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• v.19
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• pp.379-390
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• 1999

The purpose of this study is to investigate the applicability of Nakayasu & SCS method and Clark method to the computation of runoff from the river basin in Soyang watershed. As the result, each runoff was conducted to compare and analyze existing established peak flow model, and to propose a pertinent model.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.72-77
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• 2000

The purpose of this study were to monitor rainfall and runoff data from paddy blocks and forest areas at the Balan Experimental Watershed, and to investigate the variations of runoff characteristics with different land use. Field data showed that the total runoff from paddies and forest areas are not significantly different in volume. The peak discharge from forest areas was less than that from paddies for lighter storms, but became greater for heavier storms. The results demonstrate that paddies play an important role to reduce peak discharge from heavy storms as compared to forest.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2000.10a
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• pp.126-131
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• 2000

This paper presents a framework for developing an object-oriented system for runoff analysis. The objects include rainfall, meterorologic, watershed, reservoir, stream, DB management, and GUI. Data and method of each object were analyzed and defined. The database for runoff analysis were designed and DBMS MS-Access was chosen. The system design features and implementation are described, and an graphic user interface for flood runoff is presented

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.3
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• pp.208-213
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• 2007

When overland flow water is small and slow, it moves down a stream slowly and we use it as available resource. However, it could not only be good for nothing but arouse an inundation if a lot of runoff pour down to stream at a torrential rain. So it is important to know how much water to flow out and be stored in soil and on land in order to predict a flood and conserve soil and water quality. We intended to develop the prediction model of runoff in upland at a torrential rain and conducted lysimeter study in soybean cultivation and bare soil with 3 slopeness, 3 slope length and 5 soil texture from 1985 to 1991. The data of rainfall and runoff were used when daily rainfall was over 80 mm, the level of torrential rain warning. Minimum rainfall occurring runoff (MROR) was dependent on surface coverage and slope length. However soil texture and slopeness had a little influence on MROR. Runoff after MROR increased in proportion to precipitation which depended on surface coverage, soil texture and slope. Runoff ratio was larger in fine texture and bare soil than coarse soil and soybean coverage. Runoff ratio was in proportion to a square root of slope angle(radian) and reduced with slope length to converge a certain value. From these basis, we developed the prediction model following as $$Runoff(mm)=a(s^{0.5}+l^b)(Rainfall(mm)-80(1-e^{-bl}))$$ where a is a coefficient relevant soil hydraulic properties, b is a surface coverage coefficient, s is a slope angle and l is a slope length. The coefficient a was 0.5 in sandy loam and 0.6 in clay, and b was 0.06 in bare soil and 0.5 in soybean cultivation.